Algorithm-Based Runway Configuration Management: A Comprehensive ADSB Data Analysis

Airports with multiple runway options must balance efficiency and safety by selecting the best runway configuration, considering factors like traffic volume and operational demands, to ensure the smooth operation of the airport and maintain safety. This study delves into the complexities of ground dynamics at airports equipped with parallel runway configurations, employing Automatic Dependent Surveillance-Broadcast (ADS-B) data to propose enhancements in operational efficiency and safety. A multifaceted algorithmic framework was developed to dissect and interpret ADS-B data, focusing on the nuances of ground movement in various runway configurations. The study's methodology encompassed a thorough data preprocessing regime, detailed ground route analysis, precise detection of acceleration events, and the employment of cutting-edge visualization tools. Metrics such as ground times, occurrences of aircraft experiencing 'stop-and-go' events (zero-touches), apron utilization, delays, and level-off times within airport vicinities were meticulously examined. Additionally, the investigation probed into 'hot spots'—areas of heightened aircraft proximity within specified time frames, using spatial and directional analytics to gauge efficiency and safety. The study tested algorithms on an airport with parallel runways in Turkey, providing real-world insights and enhancing its relevance to operational decision-making. The results showed that first parallel runway configuration support higher air traffic volume but moderate efficiency indicators. The second parallel configuration showed reduced operational count and less efficient ground handling. The single runway configuration showed reduced operations but enhanced efficiency metrics, such as decreased zero-touch instances, average delays, acceleration event counts, and conflict potential. The analytical approach adopted herein holds promise for broad application, providing a scalable and adaptable model for airports seeking to refine their ground operation strategies. The outcomes of this study pave the way for data-driven enhancements in airport efficiency and safety, extending its utility beyond the immediate scope of parallel runway configurations